Project Documentation · v1.0

SpeedTrace Ghana

An Intelligent, Offline-First Driver Safety & Speed Tracking System for the Ghanaian Road Network

Empowering drivers with real-time intelligence — even without internet — to prevent speeding-related accidents and reckless overtaking across Ghana's 70,000+ km road network.

NRSA · Ghana Police MTTD · Ministry of Roads
PixelHive Digital Solutions
May 10, 2026
1.0 — Initial Release
This document is intended for government and institutional stakeholders. All cost figures in GHS. Confidential · Pre-Pilot Phase

Executive Summary

SpeedTrace Ghana is a mobile-based driver assistance and speed management system designed to complement existing enforcement measures such as Traffitech GH. It uniquely functions in low-internet and remote areas using offline GPS, on-device AI, and peer-to-peer mesh networking via Bluetooth and LoRa.

📡

Offline-First

Works without cellular data using GPS and pre-loaded maps

🤝

Peer-to-Peer Alerts

Drivers relay hazards via BLE mesh — no internet required

🧠

On-Device AI

TinyYOLO model detects oncoming vehicles for safe overtaking

By empowering individual drivers with actionable intelligence, SpeedTrace Ghana aims to reduce speeding-related accidents and reckless overtaking on major and rural roads throughout the country.


Problem Statement

Ghana's road network spans over 70,000 km with many sections in remote or poorly connected regions. Speeding contributes to over 50% of reported accidents (NRSA, 2024). Existing enforcement is reactive — fines arrive weeks after the offence. There is no proactive, driver-facing tool for real-time guidance, especially offline.

ProblemDescription
Limited connectivityInternet is unreliable or absent on many highways and rural roads (e.g., Eastern Region corridors, Northern Savannah routes).
Reckless overtakingPoor visibility and lack of oncoming vehicle information cause fatal head-on collisions.
No real-time feedbackDrivers only learn they exceeded speed limits when fines arrive weeks later.
No community alert systemHazards like broken trucks, potholes, and sudden rain are not shared among approaching drivers.
Underused phone sensorsModern smartphones have GPS, cameras, and Bluetooth — yet no app uses them for offline road safety in Ghana.

Proposed Solution

A free-to-use mobile application for Android and iOS with an optional low-cost hardware extension (LoRa dongle). It operates in three connectivity modes:

Offline Core

GPS speed limit warnings, pre-downloaded maps, on-device AI vehicle detection

Peer Mesh (BLE)

Direct phone-to-phone hazard relay within 100–300 m — no internet required

Extended Range (LoRa)

Hazard data relay up to 10 km, ideal for remote convoys and rural roads

The app does not replace enforcement but complements it by reducing the need for fines through voluntary compliance and driver-to-driver safety networks.


Core Features & Functionalities

Offline Speed Limit Monitoring

  • Pre-loaded geofenced speed limits derived from NRSA and open data sources
  • Audible and visual alert when exceeding the limit (customisable thresholds)
  • "Pilgrim mode": records trip speeds and offers a weekly safe driving score, synced when internet is available

On-Device AI Vehicle Detection (Overtaking)

  • Uses phone's rear camera (dashboard-mounted) with a lightweight TinyYOLO / MobileNet neural network
  • Detects oncoming vehicles and estimates time-to-collision during overtaking attempts
  • Flashing red warning and beep when unsafe overtaking is detected

Offline Peer Mesh Hazard Alerts

  • Drivers tap an icon to report: accident, breakdown, pothole, police checkpoint, fog, or rain
  • Report propagates phone-to-phone using BLE mesh — no internet required
  • Incoming warnings appear as voice notification and map pin within 1–2 seconds

Optional LoRa Extension

  • Small USB-C dongle at ¢200–300 one-time cost with optional solar repeater
  • Enables hazard exchange up to 5–10 km in open rural terrain
  • Creates a virtual "emergency broadcast corridor" for convoy operations

Optional Connected Mode

  • Syncs trip data to NRSA / DUR for traffic analytics when internet is available
  • Safe-driving leaderboards and social competition among regional drivers
  • Receives official police camera location warnings via Traffitech GH integration

USSD Bridge for Feature Phones

  • Basic USSD code (*714#) allows SMS-based blackspot warnings on pre-subscribed routes
  • No smartphone or internet required — reaches the widest possible driver audience

Technical Architecture

The system is built on an offline-first data model where all core functions rely on local SQLite or shared preferences. Cloud connectivity is entirely optional.

LayerTechnologyRangeData TypeInternet Required?
SelfGPS + on-device AIN/ASpeed, overtaking riskNo
Local PeerBLE mesh100–300 mText hazard reportsNo
Extended PeerLoRa2–10 kmText + low-res locationNo
Cloud Sync4G/5G/Wi-FiUnlimitedTrip logs, updates, scoresYes

Central backend (Django / Firebase) handles speed limit database updates, anonymised traffic flow aggregation, user accounts, and safe driving scores — only when connectivity is available.


Implementation Phases

0
Months 1–2

Feasibility & Prototyping

Validate BLE mesh performance on Tema Motorway. Train TinyYOLO on local vehicle types (taxis, trotros, SUVs, trucks). Develop minimal viable app with offline GPS speed alerts and manual BLE hazard reporting.

1
Months 3–6

Pilot Deployment — Accra–Kumasi Highway

500 drivers recruited via GPRTU and social media (200 commercial, 300 private). 50 LoRa dongles distributed to early adopters. Success target: 80% of participants report reduced speeding and fewer unsafe overtakes.

2
Months 7–12

Regional Rollout

Extend to Western, Central, Ashanti, and Northern Regions. Integrate Traffitech GH camera locations. Launch USSD bridge (*714#). Partner with Tecno and itel for pre-installation on new devices.

3
Year 2

National Coverage & LoRa Infrastructure

Deploy 500 solar-powered LoRa repeaters along accident-prone corridors (5 km intervals). Enable government dashboards for anonymised traffic density. Mandate for commercial fleet operators including haulage, STC, and intercity buses.

4
Year 3+

Continuous Improvement

AI model improvements for pedestrian and animal detection. Integration with emergency services (automated crash alert to 112). Insurance discounts for drivers with high safety scores.


Stakeholders & Partnerships

StakeholderRoleContribution
NRSALead RegulatorProvide speed limit data, enforce complementary measures, endorse the application
Police MTTDEnforcement PartnerShare anonymised camera locations, receive crash reduction reports
GPRTUUser AdoptionTrain drivers, encourage voluntary participation and uptake
Mobile Money (MVIP)IncentivesIntegrate small toll discounts for safe drivers with high scores
MTN / Vodafone / ATUSSD & DataHost USSD bridge, zero-rating for app updates
MEST / Kumasi HiveDevelopmentBuild and maintain the app and LoRa integration
Bloomberg / WHOFunding & TASupport pilot and rural LoRa infrastructure financing

Budget Estimation (First 18 Months)

App Development (Android + iOS)
Local team of 4 developers
GHS 350,000
AI Model Training & Optimisation
Training on local Ghanaian vehicle images
GHS 120,000
LoRa Dongles — Pilot (500 units)
Bulk purchase at ~¢200 each
GHS 100,000
LoRa Repeaters — Phase 3 Prep (50 units)
Solar + pole installation
GHS 250,000
BLE Mesh Middleware & Testing
Open source adaptation
GHS 80,000
USSD Gateway Integration
Per telecom partner
GHS 50,000
Marketing & Driver Training
Radio jingles and GPRTU workshops
GHS 200,000
Contingency (15%)
Buffer for unforeseen costs
GHS 180,000
Total Estimated Budget (18 months) GHS 1,330,000 ≈ USD 110,000

Funding sources include the government road safety budget, World Bank Global Road Safety Facility grants, and telecommunication CSR programmes.


Risk Assessment & Mitigation

Low Driver Adoption

Medium probability

HIGH IMPACT — Mitigated by partnering with GPRTU, offering in-app rewards, and zero-data updates for users.

Poor BLE Performance

Medium probability

MEDIUM IMPACT — Fallback to LoRa; Wi-Fi Aware available on newer Android devices as secondary option.

Battery Drain from AI Camera

High probability

MEDIUM IMPACT — AI activates only when overtaking intent is detected via turn signal or sudden lane change.

Privacy Concerns

Low probability

HIGH IMPACT — All hazard reports anonymised; no continuous location tracking; opt-in data sharing model.

Cameras Missing on Vehicles

High probability

LOW IMPACT — Core offline GPS and peer alerts function without camera AI, which is treated as optional.

Regulatory Approval Delays

Medium probability

MEDIUM IMPACT — Engage NRSA and Police from Phase 0; obtain no-objection letter before pilot launch.


Expected Impact & KPIs

Measurable targets for Year 2 after national rollout:

≤20%
Speeding violation rate on pilot routes
↓ from 35% baseline
≤80
Head-on collisions per year (overtaking-related)
↓ from 120/year
150K
Active monthly users on the platform
↑ from 0 baseline
<3s
Average driver response time to hazard warning
Per app logs
15%
Long-distance trips with at least one peer alert shared
↑ from 0%
-15%
Reduction in emergency ward admissions from RTCs
vs. 2025 baseline

Beyond numbers: drivers in remote areas gain a sense of community safety, reducing reliance on expensive roadside enforcement infrastructure. The model is scalable to other Sub-Saharan African countries.


Conclusion & Next Steps

SpeedTrace Ghana is technically feasible, economically reasonable, and socially impactful. By transitioning from pure enforcement to enabled self-regulation using offline-ready mobile technology, Ghana can significantly reduce speeding and reckless overtaking — even in areas with no internet connectivity.

Immediate next steps to be undertaken by the project sponsor:

  1. Secure in-principle approval from NRSA and Police MTTD
  2. Assemble local technical team (Android, iOS, AI, embedded systems for LoRa)
  3. Apply for pilot funding — World Bank Safer Roads grant or Ghana Innovation Fund
  4. Conduct 2-week field test of BLE mesh on the Accra–Nsawam road
  5. Sign MOU with GPRTU for driver recruitment in the pilot phase
A note on replicability SpeedTrace Ghana's architecture is designed to be adapted for other road networks in sub-Saharan Africa with minimal modification, creating an opportunity for Ghana to lead in offline-first road safety technology on the continent.